If you haven’t already, go and read Mike’s amusing and pertinent post, World of Bioinformatics Quest: Character generation. Which one are you?
I often think that in academic research at least, there are 3 types of bioinformatics:
- Bioinformatics that provides insight into biological systems
The ideal case being that you make a computational prediction which is then confirmed experimentally. Requires close collaboration between you and wet lab colleagues. By far the rarest category.
- Bioinformatics that provides insight into biological data
An example might be a statistical analysis of the PDB to identify factors common to protein chains that interact. Often useful and may overlap with type (1) in the best cases.
- Bioinformatics that develops an algorithm or statistical procedure, but provides no insight into biology whatsoever
By far the commonest category and the most prevalent in the bioinformatics literature. Normally takes the form: (a) amass some variables, (b) build a SVM, (c) run 10-fold cross-validation, (d) report sensitivity, specificity, accuracy etc. etc. Leading to the imminent death of bioinformatics as a respected research discipline. Largely responsible for the divide between bioinformaticians and bench scientists.